While statistical techniques such as regression permit characterization of a sample of data such as a population of used cars for sale, such models do not readily accommodate certain relevant factors. For example, fair market value for a vehicle may depend on geography. However, the use of geography to restrict a data set for price estimation may reduce available data (e.g., cars list for sale) so much that reliable statistical inferences about fair market value become difficult or impossible. Similarly, factors such as the reputation of a dealer who is offering a listing may be highly relevant to a purchaser when evaluating the desirability of a particular listing, but may not yield a quantitative price adjustment that can be used for comparison to other, similar vehicles.
There remains a need for improved scoring models to assist consumers when comparing listings of used vehicles.